A 3G optimization design method for passenger car crash boxes based on crashworthiness

Abstract

The present invention discloses a 3G optimization design method for a passenger vehicle crash box based on crashworthiness, comprising the following steps: measuring the outer contour of a vehicle's rectangular crash box as a design domain for crash box optimization, and determining a cross-sectional shape of the optimized outer contour of the crash box; arranging a plurality of ribs inside the outer contour; using the material of the optimized crash box, the thickness of the outer contour, and the thickness of each rib as variables, respectively, to obtain a primary optimized crash box structure formed by a combination of multiple different variables; performing a collision test on the primary optimized crash box structure to obtain a relationship model between the combination of the material of the crash box, the thickness of the outer contour, the thickness of each rib, and the maximum energy absorption, the peak cross-sectional force, and the mass of the crash box; based on the relationship model, taking maximizing energy absorption and minimizing mass as optimization goals, and taking the peak cross-sectional force being no greater than that of the original structure as an optimization constraint, to obtain the material of the final optimized crash box structure, the thickness of the outer contour, and the thickness of each rib.

Description

Technical Field

[0001] The present invention belongs to the technical field of automobile safety and lightweighting, and in particular relates to a 3G optimization design method for an energy absorption box of a passenger vehicle based on crashworthiness. Background Art

[0002] Vehicle lightweighting plays an important role in optimizing vehicle axle load distribution, improving fuel economy, reducing emissions, and minimizing environmental pollution. However, as safety requirements continue to rise, the weight of safety components is also increasing. According to E-NCAP statistics, each increase in star rating increases the gross weight of a passenger car by approximately 5% to 15%. Therefore, how to balance these two contradictions and maximize vehicle lightweighting while ensuring safety has important theoretical research significance and engineering application value.

[0003] Polycellular thin-walled structures have been extensively studied by scholars both domestically and internationally due to their excellent energy absorption properties and lightweighting potential. Traditional research, however, primarily focuses on theoretical studies of polycellular thin-walled beams based on a predefined polycellular cross-sectional configuration. This approach fails to achieve the optimal polycellular cross-sectional configuration under specific operating conditions within a given design space. Recent research on polycellular thin-walled beam cross-sectional optimization has been primarily categorized into two main approaches: applying the HCA-TWS method to achieve cross-sectional optimization through topological optimization of polycellular thin-walled beam structures, and applying evolutionary algorithms to optimize cross-sectional design.

[0004] When applying multi-cellular thin-walled structures to vehicle body design, crash boxes are one of the most optimal structures for this application. However, traditional designs often separate cross-section design from material and thickness optimization, failing to consider the coupling between these different variables and thus failing to fully tap the structure's lightweighting potential. Summary of the Invention

[0005] The purpose of the present invention is to address the defects of the existing technology and provide a 3G optimization design method for passenger car energy absorption boxes based on crashworthiness. The present invention adopts the 3G optimization concept and takes into account the cross-sectional shape, structural material and structural thickness of the energy absorption box at the same time, aiming to achieve the most lightweight design while ensuring safety during the energy absorption box design process.

[0006] The technical solution provided by the present invention is:

[0007] A 3G optimization design method for a passenger vehicle crash box based on crashworthiness includes the following steps:

[0008] Step 1: Measure the outer contour of the vehicle's rectangular crash box as the design domain for crash box optimization, and determine the cross-sectional shape of the optimized outer contour of the crash box;

[0009] Wherein, the length of the optimized energy absorption box is consistent with the length of the rectangular energy absorption box;

[0010] Step 2: Arrange a plurality of ribs inside the outer contour, wherein the ribs are rectangular plates, the axis direction of the ribs is parallel to the axis direction of the outer contour, and the two ends of the ribs are flush with the two ends of the outer contour respectively;

[0011] Wherein, both ends of the cross section of the rib are connected to the outer contour or other ribs;

[0012] Step 3: using the material of the optimized crash box, the thickness of the outer contour, and the thickness of each rib as variables, to obtain a primary optimized crash box structure formed by combining multiple different variables;

[0013] Step 4: performing a collision test on the primary optimized crash box structure to obtain a relationship model between the combination of the crash box material, the thickness of the outer contour, the thickness of each rib, and the maximum energy absorption, the peak cross-sectional force, and the crash box mass;

[0014] Step 5. Based on the relationship model, maximizing energy absorption and minimizing mass are used as optimization goals, and the cross-sectional peak force is not greater than the original structure as the optimization constraint condition to obtain the material of the final optimized energy absorption box structure, the thickness of the outer contour, and the thickness of each rib.

[0015] Preferably, in step 1, the method for determining the optimized cross-sectional shape of the outer contour of the crash box comprises the following steps:

[0016] Step 1: Divide the design domain into finite element grids and determine the loading conditions;

[0017] Step 2: Taking the homogenization of internal energy density as the design goal, determine the optimization objective function;

[0018] Wherein, the optimization objective function is:

[0019]

[0020] Where, ρ i is the design variable for topology optimization of the i-th finite element mesh, E(ρ i ) is the energy absorption of the i-th finite element grid, N is the number of finite element grids, is the average energy absorbed by the entire finite element grid, E * 、M * are the constraint values ​​of energy absorption and volume fraction respectively;

[0021] Step 3: obtaining a mathematical model for topology optimization according to the loading conditions and the optimization objective function; solving the mathematical model using a hybrid cellular automation method to obtain an optimized result of the cross-sectional shape of the outer contour of the energy absorption box.

[0022] Preferably, E * The value range is 20~30KJ, M * ≤25%.

[0023] Preferably, before step 4, the method further includes:

[0024] Determine that the initial thickness of the outer contour of the energy absorption box is 0.7 mm, and the value range of the outer contour thickness is: 0.5 to 1.4 mm; and

[0025] The initial thickness of the ribs of the energy absorption box is determined to be 0.7 mm, and the value range of the rib thickness is: 0 to 1.4 mm.

[0026] Preferably, the material of the ribs and the material of the outer profile are both made of the same aluminum alloy material.

[0027] Preferably, in the step 4, the test sample library is established by using the DOE method, and the collision test sample data is determined by using the Hammersmith sampling method.

[0028] Preferably, in step 4, after determining the test sample data, a collision test is performed on the test sample; and based on the results of the collision test, an RBF proxy model of the combination of the material of the energy absorption box, the thickness of the outer contour, the thickness of each rib, the maximum energy absorption, the peak value of the cross-sectional force and the mass of the energy absorption box is established.

[0029] Preferably, in step 5, based on the RBF agent model, a multi-objective genetic algorithm is applied to obtain a Pareto front solution, and the material of the energy absorption box structure, the thickness of the outer contour, and the thickness of each rib are finally optimized according to the Pareto front solution.

[0030] The beneficial effects of the present invention are:

[0031] (1) The present invention simultaneously considers the cross-sectional shape, thickness of the energy absorption box structure, and material variables during the optimization process, and takes into account the coupling effect between different types of variables, thereby achieving the maximum lightweight design while ensuring safety.

[0032] (2) The present invention performs a topological optimization design on the crashworthiness of the vehicle body crash box structure and determines its external contour shape; it not only designs the crash box shape more reasonably, but also provides a basis for the selection of the polyhedral structure type.

[0033] (3) The present invention adopts DOE parameterized scripts in the DOE design process instead of manually creating relevant finite element models and manually submitting calculations; it can not only quickly and accurately generate a large number of DOE sample points required for Hammersley sampling during the optimization process, but also greatly improve work efficiency and reduce the situation where the sample points created due to human errors contain a lot of noise points. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of the 3G optimization design method for passenger vehicle energy absorption boxes based on crashworthiness according to the present invention.

[0035] FIG2( a ) is a schematic diagram of the topology optimization results of the energy absorption box according to the present invention.

[0036] FIG2( b ) shows the outer cross-sectional shape of the energy absorption box after topological optimization according to the present invention.

[0037] Figure 3(a) is a schematic diagram of the connection between the original structure of the energy absorption box and the vehicle body.

[0038] FIG3( b ) is a schematic diagram of the initial structure of the optimized energy absorption box in an embodiment of the present invention.

[0039] Figure 4 These are stress-strain curves of aluminum alloys of different grades described in the present invention.

[0040] Figure 5 This is the flow chart of the DOE parameterized script described in the present invention.

[0041] Figure 6 Schematic diagram of the optimized Pareto front according to the present invention.

[0042] Figure 7 Schematic diagram of optimization results of four solutions selected in the embodiments of the present invention. DETAILED DESCRIPTION

[0043] The present invention will be described in further detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0044] like Figure 1 As shown, the present invention provides a 3G optimization design method for a passenger car energy absorption box based on crashworthiness, and the specific implementation process is as follows:

[0045] 1. Establish model collision conditions and define evaluation responses.

[0046] A finite element simulation model was established based on the full-width frontal collision requirements stipulated by the C-NCAP regulations.

[0047] Since the primary function of a crash box is to maximize the absorption of kinetic energy from a frontal collision, the maximum energy absorbed by the crash box is used as one of the evaluation criteria. Furthermore, to ensure the sequential collapse of the front-end energy-absorbing structure, the impact force on the crash box must be moderate. Therefore, the peak cross-sectional force at the fixed position of the crash box is also used as an evaluation criterion.

[0048] Second, the Hybrid Cellular Automaton (HCA) method is used to perform topological optimization design on the crash box structure to determine the outer shape of the multi-cellular crash box structure;

[0049] The specific process is as follows:

[0050] (a) During the design process, the structural dimensions of the crash box and the front end clearance are determined by combining other vehicle body factors to determine the design domain for topology optimization.

[0051] (b) Determine the boundary conditions for topology optimization: Determine the loading conditions by constraining the degrees of freedom of the energy absorption box and adding an impact rigid body;

[0052] (c) Establish mathematical model: divide the design domain into finite element meshes, and take the homogenization of internal energy density as the design goal, which is expressed as The minimum value of and volume fraction Its mathematical expression is:

[0053]

[0054] Where, ρ i is the design variable for topology optimization of the i-th finite element mesh, E(ρ i ) is the energy absorption of the i-th finite element grid, N is the number of finite element grids, is the average energy absorbed by the entire finite element grid, E * 、M * They are the constraint values ​​of energy absorption and volume fraction respectively. Both limits are set according to needs. Usually the energy absorption is set at 20-30KJ, and the volume fraction limit is not more than 25%.

[0055] (d) Based on (a), (b), and (c), a mathematical model for the topology optimization problem of the energy absorption box is established. The mathematical model is solved using the hybrid cellular automation method to obtain the topology optimization results of the energy absorption box.

[0056] (e) Performing engineering interpretation of the topology optimization results to extract the outer contour configuration of the crash box structure. Subsequently, multiple ribs are arranged within the outer contour.

[0057] Preferably, the ribs are rectangular plates, with their axes parallel to the axes of the outer contour, and their ends flush with the ends of the outer contour. The ends of the rib cross-sections are connected to the outer contour or other ribs, and each rib cross-section terminates at its connection with the outer contour or other ribs. This configuration avoids unnecessary computational effort caused by arbitrarily placing ribs, thereby improving optimization speed.

[0058] 3. Define variables for 3G optimization of the crash box:

[0059] (a) Gauge and Geometry: The core concept for optimizing the cross-section of a multi-cell thin-walled beam is to use different inner wall (rib) and outer wall thicknesses as variables. Since the inner wall (rib) thickness can be zero, meaning the inner wall (rib) elements can disappear, optimizing the inner and outer wall thicknesses will also result in changes in the cross-sectional geometry. To reduce the number of variables and improve processing, multiple inner walls (ribs) can be set as the same design variable based on symmetry.

[0060] (b) Material Grade: Considering the difficulty of varying the material of the same multi-cell thin-walled beam, only the overall material of the multi-cell thin-walled beam is selected as a variable for the material grade.

[0061] (c) The optimization effect of the crash box structure is evaluated by the maximum energy absorption (Ecmax) and mass (Mc) of the crash box, while constraining the peak cross-sectional force (Fcmax) at the fixed position of the crash box.

[0062] 4. Establish a sample library for 3G optimization of energy absorption boxes based on the DOE method. The specific steps are as follows:

[0063] (a) Based on the optimization variables determined in step (3), n sets of experimental schemes for 3G optimization of the crash box are constructed using the DOE method. The DOE method is the Hammersley sampling method. The Hammersley point can be determined by the following formula:

[0064]

[0065] Where N is the number of sampling points, z is a non-negative integer represented by a polynomial, (p1, p2, p…3, p,-n() represents any sequence, Φ p (z) is a function of z.

[0066] (b) Perform numerical calculations on n groups of experimental schemes and establish a sample library;

[0067] (c) Develop a DOE parameterization script using Python programming language for steps (a) and (b), automatically generate a key file for calculation based on the sample data, and then automatically submit all sample points for calculation in batches. The specific process is as follows:

[0068] First, we use the Hammersley sampling criterion to generate sample points, then save the variable data of these sample points in an Excel spreadsheet. We then use the xlrd module to read the spreadsheet data. Based on the initial key file, we automatically generate a key file for calculations based on the sample data. We then automatically submit all sample points for batch calculations. Finally, we output various responses, including mass, collision force, and absorbed energy, to evaluate the optimization results, as needed.

[0069] Fifth, the radial basis function neural network method was applied based on the DOE sample data to construct a proxy model of the relationship between the maximum energy absorption (Ecmax), mass (Mc), peak cross-sectional force (Fcmax) and 3G variables.

[0070] (a) The RBF surrogate model has higher prediction accuracy than other surrogate models in linear, weak nonlinear and strong nonlinear situations. The typical radial basis function expression is:

[0071]

[0072] Where λ K is the weight coefficient of the sample point, is the basis function, r K From point x to point x k The Euclidean distance.

[0073] (b) Evaluate the accuracy of the proxy model. 2 It can reflect the overall fitting accuracy of the proxy model to a large extent. Since the RBF proxy model will pass through every fitting sample point, that is, R 2 It is always 1, so for the RBF surrogate model, the R corresponding to the initial sample matrix is ​​used. 2 It is meaningless to evaluate the accuracy of the proxy model based on the cross-validation method, so the cross-validation method is used for accuracy evaluation in the evaluation process, that is, the sample information is divided into two groups according to a certain proportion, one group is used to construct the proxy model, and the other group is used for accuracy evaluation.

[0074] 6. Using Genetic Algorithms for Multi-Objective Optimization

[0075] (a) Multi-objective optimization problems (MOPs), also known as multi-standardization problems, are a branch of mathematical programming. When several nonlinear objectives exist within the same problem model and these objective functions need to be optimized simultaneously (and these objectives may conflict with each other), this problem is called a multi-objective optimization problem. Its mathematical expression can generally be expressed as follows:

[0076]

[0077] in, is called the n-dimensional decision variable vector; f m (x) represents the mth objective function to be optimized, is called the m-dimensional objective function vector; g i (x) and h j (x) represents p inequality constraints and q equality constraints respectively; F(x): R n →R m represents m mappings from the decision variable space to the objective space. Unlike single-objective optimization problems with only one objective function, MOPs do not have a unique optimal solution. Instead, they weigh and compromise each sub-objective to ultimately find a set of Pareto optimal solutions.

[0078] (b) Based on the constructed agent model, a multi-objective genetic algorithm is applied to perform 3G optimization design of the multi-cellular energy absorption box structure section. The design objectives are to maximize Ecmax and minimize Mc, while constraining Fcmax to be no greater than the original structure. The mathematical expression is:

[0079]

[0080] Among them, Ecmax, Fcmax and Mc are the maximum energy absorption, peak cross-sectional force and mass of the energy absorption box respectively; t1, t i are the outer and inner wall thicknesses of the multi-cellular thin-walled beam respectively; m, e, and f are the constraint values ​​of related parameters set according to design requirements.

[0081] 7. Verify the solution results and analyze the optimization effect.

[0082] Example

[0083] In this embodiment, a certain passenger car was selected to perform 3G optimization design on its crash box, and the improvements in relevant performance of the crash box before and after optimization were compared to demonstrate the superiority of the 3G optimization method.

[0084] 1. The research object is a front-engine, front-wheel drive B-class passenger car. A finite element simulation model is established according to the full-width frontal collision requirements stipulated by the C-NCAP regulations. The vehicle hits a rigid wall at a speed of 50km / h, and the model calculation termination time is 120ms.

[0085] The simulation results of maximum energy absorption (Ecmax) and peak cross-sectional force (PCF) are shown in Table 1:

[0086] Table 1 Quantitative comparison between substructure and whole vehicle

[0087]

[0088] Second, a hybrid cellular automation (HCA) method was used to optimize the crash box's structural topology. Based on the original crash box's dimensions and the frontal clearance, a rectangular parallelepiped with a side length of 90 × 90 mm and a length of 126 mm was used as the design domain. All six degrees of freedom (DOFs) of all nodes at the bottom of the crash box were constrained. Based on the original vehicle's energy absorption, a 207 kg rigid body was used to impact the crash box at 50 km / h.

[0089] Using the relative density of the unit cells as the design variable, homogenizing the internal energy density as the design goal, and constraining the energy absorption of the crash box structure, while also setting an upper limit of 25% on the mass fraction, the topological optimization results for the crash box structure are shown in Figure 2(a). The topological optimization results for the crash box reveal a distinct octagonal cross-section, which explains the outer shape of the multi-cellular crash box as an octagon, as shown in Figure 2(b). In the subsequent 3G optimization phase of the multi-cellular crash box, ribs will be added to fill the interior of the crash box.

[0090] Third, through topology optimization, the cross-sectional profile of the multi-cellular crash box was determined to be an octagon. By filling the octagonal profile with inner walls (ribs), the initial cross-sectional form of the multi-cellular crash box was determined, as shown in Figure 2(b). To ensure that the connection between the crash box, the front anti-collision beam, and the front longitudinal beam does not undergo significant changes, the new crash box structure will retain the original structure's connecting plate, as shown in Figure 3(a), and all parameters remain unchanged. The mass of the connecting plate will not be considered in the subsequent lightweighting evaluation after optimization.

[0091] In this embodiment, the outer contour of the 8 deformations is divided into 8 identical units. First, ribs are filled in one unit, and the ribs of other units are obtained by rotating the adjacent units 45 degrees around the center of the 8-deformation section (section), so that the filling structure of each 1 / 8 of the section is the same. 1 / 8 of the selected section of the multi-cellular thin-walled beam section is selected as the design unit, and the thickness design variables are set. As shown in Figure 3(b), each design unit includes seven variables t1 to t7; among them, t1 is the thickness of the outer wall of the multi-cellular energy absorption box, and t2 to t7 are the thickness of the inner wall (ribs). Since the thickness of the inner wall (ribs) can be 0, the change of the multi-cellular cross-sectional configuration can be achieved while optimizing the thickness. The aluminum grade of the overall structure of the energy absorption box is selected as the material variable. The optional options for the material variable are three different grades of aluminum alloys (numbered from 1 to 3), Al6060-T4, Al6063-T6 and Al7003-T5, and their stress-strain curves are shown as follows: Figure 4 shown.

[0092] Taking into account the structural characteristics and performance requirements of the multi-cellular energy absorption box, the 3G optimization design variables and their ranges are determined as shown in Table 2.

[0093] Table 2 3G optimization design variables of multi-cell energy absorption box

[0094]

[0095]

[0096] 4. Apply the Hamsley sampling criterion to generate (8+1)×(8+2)=90 sample points, calculate the sample points, and use the DOE parameterized script for automatic modeling and calculation. The specific process is as follows Figure 5 Some sample point parameters and results are shown in the table.

[0097] Table 3 DOE matrix

[0098]

[0099] 5. Based on the DOE sample data, the RBF method was used to construct the surrogate model, and the accuracy of the surrogate model was evaluated by cross validation (CV). The R values ​​of Ecmax, Fcmax and Mc were 2 are 0.9793, 0.9883 and 1.0000 respectively. 2 From the perspective of , the proxy model has higher accuracy.

[0100] 6. Based on the constructed agent model, a multi-objective genetic algorithm is applied to perform 3G optimization design of the multi-cellular energy absorption box structure section, setting the maximization of Ecmax and minimization of Mc as the design goals, while constraining Fcmax to be no greater than the original structure. The optimization mathematical expression is as follows:

[0101]

[0102] The Pareto frontier obtained by the multi-objective genetic algorithm is as follows Figure 6 As shown in the figure, for a more intuitive presentation, the energy absorption is represented as a negative value. Since two material solutions appear on the Pareto front, the Pareto front is clearly divided into two parts. It should be noted that all solutions on the Pareto front contribute to varying degrees of improvement in the proposed optimization objective compared to the original structure.

[0103] Each of the two material parts mentioned above that contains a single optimal solution is analyzed, and its basic parameters and relative positions on the Pareto front are as follows: Figure 7 As shown. In terms of changes in inner wall thickness and cross-sectional configuration, t3 and t4 mostly adopt the minimum value within the optional range or are 0, while the thickness of t2 and t5 is significantly higher. In addition, the solution sets under the two material schemes also have different thickness distribution and cross-sectional configuration characteristics. In terms of material selection, compared with Al6063-T6, Al7003-T5 has stronger energy absorption and lightweight potential. It can be seen on the Pareto frontier that almost all optimization schemes below 0.5kg choose Al7003-T5, and the weight of the 3804 optimization results with the smallest mass is even as low as 0.346kg. However, due to the limitation of cross-sectional force, the high energy absorption schemes all choose Al6063-T6 aluminum alloy. Therefore, in the specific application process, it is necessary to select the appropriate optimization scheme on the Pareto frontier based on the performance design requirements and process manufacturing conditions.

[0104] The results of the 3G optimization schemes are summarized in the table below. While energy absorption is increased, the mass of the energy absorption box is reduced to varying degrees. While some schemes exhibit higher Fcmax peaks than the original structure, they remain within acceptable limits and do not significantly impact the sequential crushing of the front-end structure. Subsequent additions of triggering mechanisms such as "crush ribs" can also significantly reduce Fcmax. Overall, the 3G optimization of the multicellular structure has achieved significant improvements.

[0105] Table 4 Comparison of schemes

[0106]

[0107]

[0108] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. A 3G optimization design method for passenger car crash boxes based on crashworthiness, characterized in that: The steps include: Step 1: Measure the outer contour of the vehicle's rectangular crash box as the design domain for crash box optimization, and determine the cross-sectional shape of the optimized outer contour of the crash box; Wherein, the length of the optimized energy absorption box is consistent with the length of the rectangular energy absorption box; Step 2: Arrange a plurality of ribs inside the outer contour, wherein the ribs are rectangular plates, the axis direction of the ribs is parallel to the axis direction of the outer contour, and the two ends of the ribs are flush with the two ends of the outer contour respectively; Wherein, both ends of the cross section of the rib are connected to the outer contour or other ribs; Step 3: using the material of the optimized crash box, the thickness of the outer contour, and the thickness of each rib as variables, to obtain a primary optimized crash box structure formed by combining multiple different variables; Step 4: performing a collision test on the primary optimized crash box structure to obtain a relationship model between the combination of the crash box material, the thickness of the outer contour, the thickness of each rib, and the maximum energy absorption, the peak cross-sectional force, and the crash box mass; Step 5: Based on the relationship model, maximizing energy absorption and minimizing mass are used as optimization goals, and the cross-sectional peak force is not greater than that of the original structure as an optimization constraint, to obtain the material of the final optimized energy absorption box structure, the thickness of the outer contour, and the thickness of each rib; In step 1, the method for determining the cross-sectional shape of the outer contour of the optimized crash box includes the following steps: Step 1: Divide the design domain into finite element grids and determine the loading conditions; Step 2: Taking the homogenization of internal energy density as the design goal, determine the optimization objective function; Wherein, the optimization objective function is: Where, ρ i is the design variable for topology optimization of the i-th finite element mesh, E(ρ i ) is the energy absorption of the i-th finite element grid, N is the number of finite element grids, is the average energy absorbed by the entire finite element grid, E * 、M * are the constraint values ​​of energy absorption and volume fraction respectively; Step 3: obtaining a mathematical model for topology optimization according to the loading conditions and the optimization objective function; solving the mathematical model using a hybrid cellular automation method to obtain an optimized result of the cross-sectional shape of the outer contour of the energy absorption box.

2. The 3G optimization design method for passenger vehicle crash boxes based on crashworthiness according to claim 1 is characterized in that: E * The value range is 20~30KJ, M * ≤25%.

3. The 3G optimization design method for passenger car crash boxes based on crashworthiness according to claim 2 is characterized in that: Before step 4, the method further includes: Determine that the initial thickness of the outer contour of the energy absorption box is 0.7 mm, and the value range of the outer contour thickness is: 0.5 to 1.4 mm; and The initial thickness of the ribs of the energy absorption box is determined to be 0.7 mm, and the value range of the rib thickness is: 0 to 1.4 mm.

4. The 3G optimization design method for a passenger vehicle crash box based on crashworthiness according to claim 3 is characterized in that: The material of the ribs and the material of the outer profile are both made of the same aluminum alloy.

5. The 3G optimization design method for a passenger vehicle crash box based on crashworthiness according to claim 3 or 4, characterized in that: In the step 4, the DOE method is used to establish a test sample library, and the Hammersmith sampling method is used to determine the collision test sample data.

6. The 3G optimization design method for passenger vehicle crash boxes based on crashworthiness according to claim 5, characterized in that: In step 4, after determining the test sample data, a collision test is performed on the test sample; and based on the results of the collision test, an RBF proxy model is established for the combination of the material of the energy absorption box, the thickness of the outer contour, the thickness of each rib, and the maximum energy absorption, the peak value of the cross-sectional force, and the mass of the energy absorption box.

7. The 3G optimization design method for passenger vehicle crash boxes based on crashworthiness according to claim 6, characterized in that: In step five, based on the RBF agent model, a multi-objective genetic algorithm is applied to obtain a Pareto front solution, and the material of the energy absorption box structure, the thickness of the outer contour, and the thickness of each rib are finally optimized according to the Pareto front solution.

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